1. Field of the Invention
The present invention relates generally to microscopy, and more particularly to ultraviolet and near ultraviolet microscopy, and still more particularly to a microscope having an objective lens and illumination system configured in combination such that the illumination system illuminates a specimen through a different region of the objective lens than that used for observation.
2. Background Discussion
Much of biological research, neuroscience research, artificial general intelligence research, and numerous other relatively exotic and esoteric areas of research are now substantially “hung up” on practical technological limitations; to with, the lack of suitable equipment and instrumentation. The limitation resides most particularly in the present inability to “functionally diagram” tissue, especially brain tissue. When it becomes available, functional diagramming may be as transformative to neuroscience and several other fields as were computers.
To date, the most ambitious functional diagramming project was performed manually. It involved diagramming the 302 neurons in the nematode (roundworm), Caenorhabditis elegans. The database is now on-line. Unfortunately, without the capabilities of the UV CT microscope and the method of using it, as described herein, that database does not include component values. And without component values, researchers are unable to label even the neurons with any detail beyond neuron type: “sensory”, “interneuron”, and “motor.”
Cognition is primarily concerned with interneuron functionality, which is determined by component values, such as synaptic efficacy. The same neuron in different subjects may have different functions, as the operation of each neuron may result from self-organization. Hence, a useful analysis would have to be completed on a single subject, which precludes all but fully automated methods.
Each synapse likely has several quantitative component values. Aside from efficacy, there may be a variety of statistical accumulators that control changes (learning), nonlinearities that may be needed for certain computations, synaptic integration and/or differentiation, along with other as-yet unknown characteristics.
Many informal proposals have been made for methods of diagramming. The primary challenge in diagramming is that each method produces neuron images differently, so that gaining understanding of the operation of living tissue using one method may not be transferable to other methods for diagramming. However, when the functionality of neurons and synapses is more fully understood, diagramming methods unusable on tissue (e.g. scanning electron microscopy) might indeed become applicable and may even produce superior diagramming results.
Diagrams are needed to understand neurons, and neuronal understanding is needed to produce better diagrams. This proposition expresses the next logical step on the long path to complete neuronal understanding, leading to the production of accurate functional diagrams.
Moreover, better understanding of neuronal function is expected to lead to mathematical algorithms to “fill in” and “clean up” what the present invention “sees,” to produce a result that far exceeds the imaging capabilities of the present invention.
The fundamental limitation in resolution is approximately ⅓ of the wavelength used for illumination or observation. This limitation applies to all methods, from MRI to electron microscopes. Like most tissue, brain tissue is transparent to radiation of nearly all wavelengths into the near UV region, whereupon the tissue becomes opaque. Due to this transparency to visible light, it is possible to directly observe the veins in one's wrist. Opacity to shorter wavelengths is the basis of Lasik eye surgery, as its use of short wavelength UV affects only the surface cells.
For diagramming purposes, observation must be made at near-UV wavelengths to utilize transparency at maximum possible resolution. Alternatively, methods not relying on transparency must be employed. Unfortunately, not enough is known to understand what might be seen at higher resolutions. Without transparency, there is presently no known way to observe detail in living neurons, a necessary requirement to close our present gap between form and function.
Near-UV has another advantageous feature for this application; namely, that in addition to being able to see near-UV light scattered by the interfaces between transparent structures having differing indexes of refraction, complex molecules naturally fluoresce when exposed to near-UV. Their natural fluorescence provides for a limited chemical analysis of complex molecules at points in tissue—a feature not available with other methods. Conventional subtractive staining provides fluorescence, but it hides structures beneath the stained details, making it unusable for diagramming.
The problem in using natural fluorescence is that it is extremely weak, due to the low number of fluorescing molecules present in complex tissue. It has been observed in the laboratory, e.g., observing fluorescent flashing from living neurons as they operate, but only low quality images using complex setups have been produced, and this has precluded its use in diagramming. It is the object of the present invention to bypass this historical barrier.
It would appear, then, that it would be advantageous to diagram utilizing near UV scattered light and fluorescent microscopy techniques. However, there is a residual problem. Present confocal microscopy methods fail to produce images of sufficient quality from bulk tissue to use for automated diagramming. The present invention advances a method of utilizing common focus microscopy, separated point scanning, and UV computed tomography (UV CT) to overcome those shortcomings.
In the late 1960s, Marvin Minsky of MIT's AI lab developed the first working machine vision system able to successfully parse visual scenes, thereby paving the way for the sorts of brain diagramming now contemplated. Marvin Minsky also invented the confocal microscope. Soon after there was an early effort at Carnegie Mellon University to diagram insect brains using a computer program written by Michael Everest. Researchers attempted to microtome slices of the brains and to stain them for microscopic scanning using 2D visible light methods. The effort failed because some slices were inadvertently destroyed, and staining is a subtractive process (whereas scatter and fluorescence are additive) so that it was impossible to see anything behind a stained detail. Further, large microtome slices must be >4μ thick to withstand handling, but some important parts of neurons (axons, for instance) may only be 1μ or less wide. The present invention provides more than an order of magnitude more real-world resolution than prior methods by working in 3D with ultraviolet, and uses UV CT to extract more detail than present visual methods can extract.
To date there have been no successful automated brain diagramming projects. Automated brain diagramming appears to be impossible until microscopes similar to the present invention are available. To diagram brains, such a microscope will require the largest supercomputers now available to deal with the overwhelming computational load that can produce whole-brain diagrams in months, rather than centuries.
It may prove impossible to fully diagram brains through observation alone, as the present invention seeks to do, and this would be due to structural details not microscopically observable at practical speeds by any conceivable method. It is hoped and expected, however, that other methods not based on observation will provide the missing details, e.g., by applying analytical methods to infer that which cannot be seen.
Background Technology:
Perhaps the best discussion of the technical background can be found at the Carl Zeiss Microscopy Online Campus web page, entitled, “Digital Imaging Considerations” [see http://zeiss-campus.magnet.fsu.edu/print/spinningdisk/introduction-print.html]. Therein, the best prior art methods, those utilizing lasers and Petrá{hacek over (n)} disks, are discussed for digitally imaging tissue. These methods do not utilize the methods and apparatus of the present invention. The present invention is an optical improvement independent of the scanning method.
Note that there are speed problems in performing fast real-time scanning with a single moving spot. This can be easily eliminated in systems with an intelligent pseudo-random scanning capability, because not every point must be scanned with every frame. All that must be scanned with every frame are points around various edges to identify when, and in what direction, they move, and one point within each structure to identify when its chemistry changes. Changes in these parameters would then trigger other localized scanning. This will speed up the scanning process by 100:1 or more.